| DOI | Resolve DOI: https://doi.org/10.1007/978-3-540-74976-9_40 |
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| Author | Search for: Drummond, Chris1 |
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| Affiliation | - National Research Council of Canada. NRC Institute for Information Technology
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| Format | Text, Article |
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| Conference | European Conference on Principles of Data Mining and Knowledge Discovery, Databases, September 17-21, 2007, Warsaw, Poland |
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| Subject | pressure ratio; morphological operation; shape space; speed line; turbofan engine |
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| Abstract | This paper shows how multi-dimensional functions, describing the operation of complex equipment, can be learned. The functions are points in a shape space, each produced by morphing a prototypical function located at its origin. The prototypical function and the space’s dimensions, which define morphological operations, are learned from a set of existing functions. New ones are generated by averaging the coordinates of similar functions and using these to morph the prototype appropriately. This paper discusses applying this approach to learning new functions for components of gas turbine engines. Experiments on a set of compressor maps, multi-dimensional functions relating the performance parameters of a compressor, show that it more accurately transforms old maps, into new ones, than existing methods. |
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| Publication date | 2007 |
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| Publisher | Springer |
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| Series | |
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| Language | English |
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| Peer reviewed | Yes |
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| NPARC number | 23002094 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 2df6f83d-4db3-408f-9218-563f6251dd59 |
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| Record created | 2017-08-14 |
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| Record modified | 2023-11-02 |
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